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Validation of a Smartwatch in Persons With Multiple Sclerosis

Primary Purpose

Multiple Sclerosis

Status
Completed
Phase
Not Applicable
Locations
Germany
Study Type
Interventional
Intervention
Comfortable walking velocity (CWV)
Slow walking velocity (SWV: CWV - 20%)
Fast walking velocity (FWV: CWV + 20%)
Sponsored by
University of Erlangen-Nürnberg
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional other trial for Multiple Sclerosis focused on measuring Multiple Sclerosis, Motion sensors, Smartwatch, Steps, Walking, Validation

Eligibility Criteria

18 Years - undefined (Adult, Older Adult)All SexesDoes not accept healthy volunteers

Inclusion Criteria:

  • Multiple Sclerosis with Expanded Disability Status Scale between 0 - 6.5
  • Ability to walk 250 steps with or without an assistive device

Exclusion Criteria:

  • Clinically relevant cardiovascular or orthopaedic disease
  • Severe polyneuropathy
  • Cognitive impairment

Sites / Locations

  • Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Department of Sport Science and Sport, Gebbertstr. 123b

Arms of the Study

Arm 1

Arm Type

Experimental

Arm Label

Walking protocol

Arm Description

Walking for 250 steps with comfortable walking velocity (CWV), slow walking velocity (SWV: CWV - 20%) and fast walking velocity (FWV: CWV + 20%) with sufficient rest between conditions.

Outcomes

Primary Outcome Measures

Step detection during comfortable walking
Step detection accuracy of the two devices (Polar M600 and ActiGraph wGT3X-BT) for both the standard algorithm and the self-developed algorithm during comfortable walking for 250 steps.

Secondary Outcome Measures

Step detection during slow walking
Step detection accuracy of the two devices (Polar M600 and ActiGraph wGT3X-BT) for both the standard algorithm and the self-developed algorithm during slow walking for 250 steps.
Step detection during fast walking
Step detection accuracy of the two devices (Polar M600 and ActiGraph wGT3X-BT) for both the standard algorithm and the self-developed algorithm during fast walking for 250 steps.

Full Information

First Posted
July 30, 2018
Last Updated
April 11, 2019
Sponsor
University of Erlangen-Nürnberg
Collaborators
Neurological Rehabilitation Center Quellenhof, ZTM Bad Kissingen
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1. Study Identification

Unique Protocol Identification Number
NCT03750097
Brief Title
Validation of a Smartwatch in Persons With Multiple Sclerosis
Official Title
Validation of a Commercially Available Smartwatch for Step Detection in Persons With Multiple Sclerosis
Study Type
Interventional

2. Study Status

Record Verification Date
April 2019
Overall Recruitment Status
Completed
Study Start Date
May 1, 2018 (Actual)
Primary Completion Date
December 15, 2018 (Actual)
Study Completion Date
January 31, 2019 (Actual)

3. Sponsor/Collaborators

Responsible Party, by Official Title
Principal Investigator
Name of the Sponsor
University of Erlangen-Nürnberg
Collaborators
Neurological Rehabilitation Center Quellenhof, ZTM Bad Kissingen

4. Oversight

Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
No

5. Study Description

Brief Summary
The study is designed to validate the accuracy of steps detected by a commercially available smartwatch in persons with multiple sclerosis. Specifically, the investigators examine whether a smartwatch can detect steps accurately during slow, comfortable and fast overground walking. The total steps counted by the smartwatch will be compared to those counted by an accelerometer commonly used in clinical studies and the actually walked steps.
Detailed Description
Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system. It is one of the most common neurological diseases in young adulthood. The main symptoms of MS are gait and mobility impairments, which also determine the severity of the disease. Currently, subjective clinical functional tests are commonly used to evaluate therapy outcomes. Due to advancing mechanization, body-worn accelerometers have been established as a potential instrument for the objective detection of mobility in clinical research. The accuracy of these devices for determining the mobility is therefore essential. However, current studies, especially in people with altered gait, show large deviations in step detection accuracy. In the present study we want to investigate: i) whether a commercially available smartwatch (Polar M600) counts steps in persons with multiple sclerosis (pwMS) accurately and ii) whether it counts steps as accurately as an accelerometer commonly used in clinical research (ActiGraph wGT3X-BT). In addition, the accuracy of the step detection by the algorithms of the manufacturer of the two devices (Polar M600 and ActiGraph wGT3X-BT) will be compared with an own-developed algorithm. For this purpose, 63 pwMS with low to severe functional restriction (EDSS: 0 - 6.5) will participate in this validation study. The validation protocol consists of three walking tests with different walking velocities. During these three conditions the participants will wear the Polar M600 on the wrist and the ActiGraph wGT3X-BT with a belt over the hip. In the first walking test, the subjects will complete 250 steps with comfortable walking velocity (CWV). After a sufficient break, the participants will be randomly assigned to either a fast walking velocity condition (FWV: CWV + 20%) followed by a sufficient period of rest and a slow walking velocity condition (SWV: CWV - 20%) or vice versa. Each of the walking tests with modified walking velocity also consists of 250 steps. To analyze the accuracy of step detection, the measured steps of the devices will be compared with the actually walked 250 steps.

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Multiple Sclerosis
Keywords
Multiple Sclerosis, Motion sensors, Smartwatch, Steps, Walking, Validation

7. Study Design

Primary Purpose
Other
Study Phase
Not Applicable
Interventional Study Model
Single Group Assignment
Masking
None (Open Label)
Allocation
N/A
Enrollment
58 (Actual)

8. Arms, Groups, and Interventions

Arm Title
Walking protocol
Arm Type
Experimental
Arm Description
Walking for 250 steps with comfortable walking velocity (CWV), slow walking velocity (SWV: CWV - 20%) and fast walking velocity (FWV: CWV + 20%) with sufficient rest between conditions.
Intervention Type
Behavioral
Intervention Name(s)
Comfortable walking velocity (CWV)
Intervention Description
Walking for 250 Steps with self-selected comfortable walking velocity while wearing the two accelerometers (Polar M600 and ActiGraph wGT3X-BT)
Intervention Type
Behavioral
Intervention Name(s)
Slow walking velocity (SWV: CWV - 20%)
Intervention Description
Walking for 250 Steps with slow walking velocity while wearing the two accelerometers (Polar M600 and ActiGraph wGT3X-BT). Slow walking consists of walking with 20% slower than the self-selected comfortable walking velocity by following a researcher who controls the walking velocity with a measuring wheel.
Intervention Type
Behavioral
Intervention Name(s)
Fast walking velocity (FWV: CWV + 20%)
Intervention Description
Walking for 250 Steps with fast walking velocity while wearing the two accelerometers (Polar M600 and ActiGraph wGT3X-BT). Fast walking consists of walking with 20% faster than the self-selected comfortable walking velocity by following a researcher who controls the walking velocity with a measuring wheel.
Primary Outcome Measure Information:
Title
Step detection during comfortable walking
Description
Step detection accuracy of the two devices (Polar M600 and ActiGraph wGT3X-BT) for both the standard algorithm and the self-developed algorithm during comfortable walking for 250 steps.
Time Frame
Following the comfortable walking velocity protocol, an average of 2 minutes
Secondary Outcome Measure Information:
Title
Step detection during slow walking
Description
Step detection accuracy of the two devices (Polar M600 and ActiGraph wGT3X-BT) for both the standard algorithm and the self-developed algorithm during slow walking for 250 steps.
Time Frame
Following the slow walking velocity protocol, an average of 2 minutes
Title
Step detection during fast walking
Description
Step detection accuracy of the two devices (Polar M600 and ActiGraph wGT3X-BT) for both the standard algorithm and the self-developed algorithm during fast walking for 250 steps.
Time Frame
Following the fast walking velocity protocol, an average of 2 minutes

10. Eligibility

Sex
All
Minimum Age & Unit of Time
18 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
Inclusion Criteria: Multiple Sclerosis with Expanded Disability Status Scale between 0 - 6.5 Ability to walk 250 steps with or without an assistive device Exclusion Criteria: Clinically relevant cardiovascular or orthopaedic disease Severe polyneuropathy Cognitive impairment
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Klaus Pfeifer, Prof. Dr.
Organizational Affiliation
Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Department of Sport Science and Sport
Official's Role
Principal Investigator
First Name & Middle Initial & Last Name & Degree
Peter Flachenecker, Prof. Dr. med.
Organizational Affiliation
Neurological Rehabilitation Center Quellenhof
Official's Role
Principal Investigator
Facility Information:
Facility Name
Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Department of Sport Science and Sport, Gebbertstr. 123b
City
Erlangen
ZIP/Postal Code
91058
Country
Germany

12. IPD Sharing Statement

Plan to Share IPD
Undecided
Links:
URL
http://www.sport.fau.de/ms-bewegt/
Description
Project webpage

Learn more about this trial

Validation of a Smartwatch in Persons With Multiple Sclerosis

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